Modelling Human Perceptual-motor Interaction for Human-machine Applications

The project aims to develop a new modelling framework for identifying the perceptual-motor processes that underlie cooperative and competitive human interaction. The project will also determine whether this modelling framework can be combined with modern machine-learning methods to develop artificial agents capable of human level performance. Expected outcomes will include a practical methodology for rapidly generating models of effective human interaction that can be easily implemented in human-machine systems. Benefits will include a richer understanding of the fundamental perceptual-motor processes that support robust human interaction and enhanced the effectiveness of human-machine collaboration and training technologies.

Advances in cyber-technology have created new opportunities for human-machine interaction. Developing artificial agents that can naturally respond to the movements and actions of human actors is essential for the success of such systems and requires identifying and modelling the perceptual-motor processes that underlie cooperative and competitive social activity. This project will identify these processes and produce a practical methodology for implementing them in interactive artificial agents. The project outcomes will be applicable across a range of research and industrial settings, and will therefore have social and economic benefits and strengthen Australia’s international standing in human-machine interaction research and development.

RECENT PUBLICATIONS:

Nalepka, P., Lamb, M., Kallen, R. W., Shockley, K., Chemero, A., Saltzman, E., & Richardson, M. J. (2019). Human social motor solutions for human–machine interaction in dynamical task contexts. Proceedings of the National Academy of Sciences, 201813164.

Lamb, M., Nalepka, P., Kallen, R. W., Lorenz, T., Harrison, S. J., Minai, A. A., & Richardson, M. J. (2019). A Hierarchical Behavioral Dynamic Approach for Naturally Adaptive Human-Agent Pick-and-Place Interactions. Complexity, p1-16, DOI: 10.1155/2019/5964632

Lamb, M., Mayr, R., Lorenz, T., Minai, A. A., & Richardson, M. J. (2018). The Paths We Pick Together: A Behavioral Dynamics Algorithm for an HRI Pick-and-Place Task. In Companion of the 2018 ACM/IEEE International Conference on Human-Robot Interaction (pp. 165-166). ACM.

Nalepka, P., Lamb, M., Kallen, R. W. & Richardson, M. J., (2018). Emergence of efficient, coordinated solutions despite differences in agent ability during human-machine interaction: demonstration using a multiagent “shepherding” task. Proceedings of the 18th International Conference on Intelligent Virtual Agents (IVA 2018). New York: Association for Computing Machinery, Inc, p. 337-338 2 p.

Lamb, M., Lorenz, T., Harrison, S., Kallen, R., Minai, A., Richardson, M. (2017) PAPAc: A Pick and Place Agent Based on Human Behavioral Dynamics. In Proceedings of the Fifth International Conference on Human Agent Interaction (HAI '17). ACM, New York, NY, US. https://dl.acm.org/citation.cfm?doid=3125739.3125771